Model comparison

DeepSeek V4 Flash vs Llama 13b

DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 24.4 on the Noometry Index.

Last verified . 9 shared benchmarks.

DeepSeek V4 Flash DeepSeek

53.6

Rank #35 Confirmed

Llama 13b Meta

24.4

Rank #348 Confirmed

Summary

  • They share 9 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 6 categories and Llama 13b in 0 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where DeepSeek V4 Flash leads 63.8 to 13.8.

Side by side

DeepSeek V4 Flash and Llama 13b specifications
DeepSeek V4 FlashLlama 13b
ProviderDeepSeekMeta
Noometry Index53.624.4
Released2026-04-242023-02-24
WeightsOpenOpen
Context window1M—
Max output393K—
Input $ / M tokens$0.15—
Output $ / M tokens$0.60—
Results tracked4121

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Category by category

Coding DeepSeek V4 Flash leads

DeepSeek V4 Flash: 47.9 (#59), Llama 13b: 21.4 (#337)

Coding benchmarks
BenchmarkDeepSeek V4 FlashLlama 13b
LMArena Coding1457683
FrontierCode18.8%—
LMArena WebDev1582—
SciCode49.9%—
WeirdML63%—
ALE-Bench1,306—

Reasoning DeepSeek V4 Flash leads

DeepSeek V4 Flash: 53.7 (#30), Llama 13b: 14.0 (#329)

Reasoning benchmarks
BenchmarkDeepSeek V4 FlashLlama 13b
LMArena Hard Prompts1444728
Epoch Capabilities Index154.49100.58
ARC-AGI-261.4%—
SimpleBench61.1%—
Kagi LLM Benchmark52.2%—
NYT Connections (extended)89.6%—
ARC-AGI-189%—
CritPt16.6%—
Chess Puzzles33%—
Mystery Game Puzzles34%—
DTBench90.9%—
LMCA41.7%—
BIG-Bench Hard—37.9%
HellaSwag—79.2%
LAMBADA—75.2%
PIQA—80.1%
WinoGrande—73%

Math DeepSeek V4 Flash leads

DeepSeek V4 Flash: 60.3 (#37), Llama 13b: 26.7 (#256)

Math benchmarks
BenchmarkDeepSeek V4 FlashLlama 13b
LMArena Math1427838
FrontierMath (Tiers 1-3)57.5%—
FrontierMath Tier 424.4%—
MathArena Final-Answer Competitions76.5%—
OTIS Mock AIME 2024-202594.4%—
ProofBench56%—
GSM8K—20.6%

Knowledge Not comparable

DeepSeek V4 Flash: 55.4 (#48), Llama 13b: —

Knowledge benchmarks
BenchmarkDeepSeek V4 FlashLlama 13b
GPQA Diamond91%—
SimpleQA Verified33.6%—
LMArena Expert1441—
ARC (AI2) Challenge—52.7%
BoolQ—78.7%
MMLU—47.7%
OpenBookQA—56.4%
TriviaQA—77.9%

Multimodal Not comparable

DeepSeek V4 Flash: —, Llama 13b: —

Multimodal benchmarks
BenchmarkDeepSeek V4 FlashLlama 13b
ScienceQA—43.3%

Multilingual DeepSeek V4 Flash leads

DeepSeek V4 Flash: 53.0 (#72), Llama 13b: 16.6 (#297)

Multilingual benchmarks
BenchmarkDeepSeek V4 FlashLlama 13b
LMArena Non-English1420819
LMArena Chinese1468—
LMArena French1439—
LMArena German1418—
LMArena Japanese1406—
LMArena Korean1384—
LMArena Russian1428—
LMArena Spanish1436—

Instruction Following DeepSeek V4 Flash leads

DeepSeek V4 Flash: 74.9 (#81), Llama 13b: 36.7 (#305)

Instruction Following benchmarks
BenchmarkDeepSeek V4 FlashLlama 13b
LMArena Instruction Following1421781

Long Context Not comparable

DeepSeek V4 Flash: 43.8 (#85), Llama 13b: —

Long Context benchmarks
BenchmarkDeepSeek V4 FlashLlama 13b
LMArena Longer Query1434—

Writing & Preference DeepSeek V4 Flash leads

DeepSeek V4 Flash: 63.8 (#61), Llama 13b: 13.8 (#312)

Writing & Preference benchmarks
BenchmarkDeepSeek V4 FlashLlama 13b
LMArena Text1432834
LMArena Creative Writing1403794
LMArena Multi-Turn1449753
EQ-Bench Creative Writing1559—

Frequently asked questions

Is DeepSeek V4 Flash better than Llama 13b?

DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 24.4 on the Noometry Index.

Is DeepSeek V4 Flash or Llama 13b better for coding?

DeepSeek V4 Flash scores higher on coding benchmarks: 47.9 versus 21.4 in the Noometry coding category.

How many benchmarks do DeepSeek V4 Flash and Llama 13b share?

9 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Llama 13b has 21.

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